1.In assessing sensitivity of D&A
results to Òmodel qualityÓ
2.By contributing state-of-the-art
space-time modeling approaches to Òfill in the gapsÓ in observational datasets
with sparse, space- and time-varying coverage
3.By helping to provide a better
assessment of the Òtrade-offsÓ between ensemble size (for any individual model)
and the number of models contributing to a multi-model average
4.By contributing improved methods for
assessing whether human influences have modulated the statistical behavior of
existing modes of natural variability
5.By bringing statistical rigor to
regression-based predictions of hurricane activity
6.Better constraining the Transient
Climate Response obtained from D&A methods